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Dawid Rymarczyk, PhD
Dawid Rymarczyk, PhD
Jagiellonian University; Data Scientist, Ardigen
Zweryfikowany adres z ii.uj.edu.pl
Tytuł
Cytowane przez
Cytowane przez
Rok
Protopshare: Prototypical parts sharing for similarity discovery in interpretable image classification
D Rymarczyk, Ł Struski, J Tabor, B Zieliński
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
91*2021
Interpretable image classification with differentiable prototypes assignment
D Rymarczyk, Ł Struski, M Górszczak, K Lewandowska, J Tabor, ...
European Conference on Computer Vision, 351-368, 2022
672022
Deep learning approach to describe and classify fungi microscopic images
B Zieliński, A Sroka-Oleksiak, D Rymarczyk, A Piekarczyk, ...
PloS one 15 (6), e0234806, 2020
64*2020
Kernel self-attention for weakly-supervised image classification using deep multiple instance learning
D Rymarczyk, A Borowa, J Tabor, B Zielinski
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021
462021
ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification
D Rymarczyk, A Pardyl, J Kraus, A Kaczyńska, M Skomorowski, ...
ECML PKDD 2022, 2022
28*2022
Protoseg: Interpretable semantic segmentation with prototypical parts
M Sacha, D Rymarczyk, Ł Struski, J Tabor, B Zieliński
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023
182023
Icicle: Interpretable class incremental continual learning
D Rymarczyk, J van de Weijer, B Zieliński, B Twardowski
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
112023
Deep learning classification of bacteria clones explained by persistence homology
A Borowa, D Rymarczyk, D Ochońska, M Brzychczy-Włoch, B Zieliński
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
9*2021
ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging
Ł Struski, D Rymarczyk, A Lewicki, R Sabiniewicz, J Tabor, B Zieliński
European Conference on Artificial Intelligence, 2210-2217, 2023
42023
Deep learning models capture histological disease activity in Crohn’s disease and ulcerative colitis with high fidelity
D Rymarczyk, W Schultz, A Borowa, JR Friedman, T Danel, P Branigan, ...
Journal of Crohn's and Colitis 18 (4), 604-614, 2024
32024
Progrest: Prototypical graph regression soft trees for molecular property prediction
D Rymarczyk, D Dobrowolski, T Danel
Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023
22023
Identifying bacteria species on microscopic polyculture images using deep learning
A Borowa, D Rymarczyk, D Ochońska, A Sroka-Oleksiak, ...
IEEE Journal of Biomedical and Health Informatics 27 (1), 121-130, 2022
22022
Interpretability benchmark for evaluating spatial misalignment of prototypical parts explanations
M Sacha, B Jura, D Rymarczyk, Ł Struski, J Tabor, B Zieliński
Proceedings of the AAAI Conference on Artificial Intelligence 38 (19), 21563 …, 2024
12024
Automating patient-level lung cancer diagnosis in different data regimes
A Pardyl, D Rymarczyk, Z Tabor, B Zieliński
International Conference on Neural Information Processing, 13-24, 2022
12022
Multimodal Approach to MoA Prediction Based on Cell Painting Imaging and Chemical Structure Data
M Koziarski, P Gaiński, K Rataj, A Borowa, K Wójtowicz, J Gwóźdź, ...
1
Decoding phenotypic screening: A comparative analysis of image representations
A Borowa, D Rymarczyk, M Żyła, M Kańdula, A Sánchez-Fernández, ...
Computational and Structural Biotechnology Journal 23, 1181-1188, 2024
2024
Interpretable deep learning with prototypical parts for supervised and weakly-supervised learning
D Rymarczyk
2024
Token Recycling for Efficient Sequential Inference with Vision Transformers
J Olszewski, D Rymarczyk, P Wójcik, M Pach, B Zieliński
arXiv preprint arXiv:2311.15335, 2023
2023
CompLung: Comprehensive Computer-Aided Diagnosis of Lung Cancer
A Pardyl, D Rymarczyk, J Jaworek-Korjakowska, D Kucharski, A Brodzicki, ...
European Conference on Artificial Intelligence, 1835-1842, 2023
2023
Comparison of Supervised and Self-Supervised Deep Representations Trained on Histological Images
D Rymarczyk, A Borowa, A Bracha, M Chronowski, W Ozimek, B Zieliński
MEDINFO 2021: One World, One Health–Global Partnership for Digital …, 2022
2022
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